2023 Volume 11 Issue 4 Pages 167-184
This empirical study identifies the characteristics and roles that regulate the collaborative policy network for handling the urban slum settlements in Pekanbaru. The method used in this study is quantitative methods through semi-structured surveys. Questionnaires were utilised to produce the indicators related to the structure of relationships and roles between the leading figures that were graphically depicted through social network analysis and have been confirmed in every stage of the program through centrality analysis. The results indicate that the collaborative policy network on handling the urban slum settlements leads to the formation of public and community figures. The number of figures is relatively stable, and the pattern of relationships among the figures shows the complex dynamics. However, along the progressed program, the distance and density of relationships among the figures at each stage keep decreasing. Receiving and mediating information and resources is centralised to local government. Local government emerged as a community figure that plays an essential role in the network. It indicates the importance of equal distribution of resources and information to maintain the stability of relations and distances among public figures.
The problem of urban slums is challenges, especially in providing services and an excellent infrastructural base. The challenges were responded to by the Indonesia government in 1969 through various policies such as the Kampung Improvement Program (KIP), Community-Based Housing Development (P2BPK), Urban Poverty Alleviation Program (P2KP), Community-Based Initiatives for Housing and Local Development (COBILD), Neighbourhood Upgrading and Shelter Sector Project (NUSSP), and National Community Empowerment Program (PNPM). However, those policies have not significantly impacted the slums’ improvement.
The main problem with these policies is the top-down method and less observing the stakeholders’ role. Hence, it needs a different approach through a policy network between the government, private sector, community, academia, and the media. Politics, society, and culture made the different policies in Indonesia. Moreover, the policies aim to increase active participation in the level of local society and make the local government the leading actor.
During the enactment of Law Number 9/2015 concerning Regional Government, there has been a transformation in the role of local government. The regional government acts as the leading community figure in a city program of slums-free policy (KOTAKU). It aims to encourage decision-making for Indonesia’s lowest units of government organisations. Therefore, they can quickly respond to the community’s problems, demands and needs; thus, the development and public services in each region can be carried out effectively and efficiently (UU9, 2015).
These issues related to the impact of regional social, economic and political changes that led to the decentralisation and complexity of environmental policies. Therefore, the planning and implementation of urban slum management policies should be carried out on a multilateral basis, involving various organisations and departments. Due to the limited resources of the local governments, actions cannot be taken effectively. Additionally, the slum governance policy experiences a change of top-down approach and a fundamental programmatic shift towards a broader transition of decentralisation and people-driven development (B. Sharma, S. Sharma, et al., 2022).
The slums are a complex issue that needs various actors to be involved, such as government, academia, society, private and the media and sectors such as the land sector, the planning of building and spatial, and the provision of settlement infrastructure. This complexity originates from various problems and challenges in collaborative policy networks, such as resource dependency, actor interaction, and the realisation of government institutional fragmentation.
In order to recognise the interconnected policies and complex environments, several researchers (Ingold and Leifeld, 2014; Richardson, 2015b) have advocated policy implementation through the network approach. Policy network is a loose term that refers to the interdependent relationship between two organisations and individuals who often contact each other within certain policies (Axelsson and Easton, 2016) (Yeatman, 2020).
The policy network to overcome urban slum settlements in Pekanbaru is formulated and implemented through the involvement and interaction of various organisations and sectors, including every public figure involved in the KOTAKU program as a network of urban slum policies (Zhan, Fan, et al., 2018). In this sense, the implementation of the KOTAKU policy is a dynamic and complex process (Dredge, 2006a, 2006b; Mason, 2020; Pforr, 2005, 2006). A group of actors interact, communicate, and develop complex relationships during the KOTAKU program. The interacting group of public figures is called as policy network (Ingold and Leifeld, 2014; Richardson, 2015a; Sorensen and Torfing, 2007; Sullivan and Skelcher, 2017). In short, the KOTAKU policy occurs within the network of public figures.
The dominance of local government as the leading figure in policy networks is also found in the research of Zhang (Zhang, Fan, et al., 2019) regarding the environmental problems in China. This research showed that the strength of the Chinese government in its environmental policy exists in the role of local governments as the leading organisation to promote the policy.
Furthermore, the Pekanbaru Government issued Regional Regulation Number 13/2016 concerning the prevention and improvement of quality in the slum urban settlement. The urban slum-free policy is a policy that becomes a platform or a basis for solving the slum settlements, integrating various resources of local government, private sector, society and other stakeholders to build an integrated system where local governments collaborate with other stakeholders in every stage —starting from the preparation, planning and implementation stages by prioritising citizen participation (Perda 13, 2016).
The formation of collaborative processing in urban slum settlements is a critical issue to be discussed. Therefore, an understanding of collaboration networks is required. Environmental policies dealing with urban slums near local governments are changing rapidly. Local governments do not decide the planning and implementation of urban slum management policies but the stakeholder management instead (Pramono, Palupi, et al., 2022). In other words, it is imperative to understand the stakeholder networks because of the complexity of the decision-making process and the number of citizens involved.
The Policy Network effectively analyses the complex connections and interactions between stakeholders and has another function as a method of categorising the relationships. Previous research has been conducted on policy network studies (Howlett, 2019; Huxman and Vangen, 2013; Rethemeyer and Hatmaker, 2008; Robinson, 2006; Varda, 2009). However, these studies focus more on policymaking. A collaborative network analysis study approach in the process of implementing city policies, especially in the urban slum area, is still lacking, while such policy is very important. Thus, it is necessary to conduct an empirical analysis of policy networks’ characteristics and roles, focusing on collaborative network analysis to cope with the urban slum settlement. The program of KOTAKU 2016 is a collaborative case in solving the urban slum, which aims to create habitable settlements by 2019.
Urban slums are used to describe various low-income settlements or poor human living conditions. This inadequate housing condition is illustrated as a manifestation of urban poverty, where the population is dense and the housing and poverty are below the standard (UN-Habitat, 2003). This definition summarises the important characteristics of slum areas, such as high density and low house structure standards (structure and services) and poverty. The first two criteria are related to physical and spatial, while the third criteria are social and behavioural.
Cooperation in dealing with urban slum settlements emphasises the role of local governments, which is to guide and promote various forms of cooperation among stakeholders by prioritising citizens as subjects of active development. It is collaborated through a participatory approach, combining the macro (top-down) planning and micro (bottom-up) planning processes. The planning is developed based on not only the current problem solution but also the vision of real life to realise a city worth living in and adapted to the vision of urban space planning.
Policy networkPolicy network study is a study that is currently being developed, not only in business organisations but also in public organisations. The organisation used in the network approach is an organisation that always believes other organisations control the important resources; therefore, a network strategy is needed to obtain the resource dependency theory. Because they believe the strength of network governance lies in its practicality, and they argue that most classical theories fail to describe how public programs actually work, and they attempt to define the implementation policy easily.
A policy network is an abbreviation of the inter-organisational network approach. It is a regional government strategy to obtain resources and gain legitimacy from other organisations in implementing urban slum management programs in Pekanbaru. Policy network theory is used as an analytical tool to explain the complex interactions between actors and stakeholders in dealing with the settlements of urban slums. Therefore, understanding the policy network on dealing with the settlement of urban slum settlements is necessary due to the rapidly changing policy on the environment around the local governments.
A policy network can be defined as a group or complex of organisations connected to each other by dependent resources and distinguished from other groups by time in a dependent structure (Richardson, 2015a)(Axelsson and Easton, 2016). Policy networks are defined by their boundaries, figures, and interrelationships. It includes a relatively stable set of cooperative community figures, primarily public and private. The relationship among public figures is related to a communication channel for exchanging information, expertise, trust, and other policy resources. Formal institutions do not primarily determine the boundaries of a particular policy network but the result of a mutual process of recognition that depends on functional relevance and structural engagement (Rhodes, 2018). Collaborative policy network studies in housing and environment have been carried out with a focus on the process of policy making process (Gasparre, 2011; Y. Lee, I. Lee, et al., 2012; McAllister, McCrea, et al., 2014; Weare, Lichterman, et al., 2014; Zhang, Fan, et al., 2019). However, there is still a lack of empirical research on the implementation of cooperative policy networks, especially in slum areas. Therefore, it is necessary to conduct research through collaborative policy network analysis to deal with urban slum settlements.
Policy networks: social network analysisThe main objective of this study is to explore the characteristics of the network and the roles of the involved parties in a collaborative policy network to overcome the slum settlements. Network characteristics can be obtained by finding one of the more important figures than the other. The important figure can be a person who contributes to giving most of the information and resources connected to the other members and is most frequently invited to related events. This interaction can be measured through social network analysis (SNA). Social network analysis, derived from graphic theory, describes the structure of relationships between certain entities and applies quantitative techniques to produce indicators and results relevant to the characteristics of the entire network and the role of public figures in the network structure. One of the main applications of social network analysis is identifying the important public figures in their network. It can be measured through centrality (Carrington, Scott, et al., 2005).
Centrality is an indicator that shows the degree of centralisation of a figure across the network. Centrality consists of the degree and betweenness centrality. Degree centrality is divided into In-degree and Out-degree according to the direction of exchange and measured by the number of direct connections among the figures in the network. In-degree refers to accepting requests for relationships from other figures, such as recipients of information or resources. Out-degree refers to pursuing aggressive action to ask other actors to enter a relationship, such as the sender of information or resources. The inner degree centrality (CD in) and the outer degree centrality (CD out) of a particular node are formally defined in the following equation (Shih, 2006):
Where r in and r out, respectively, denote the inward and outward connections of node I, and l denotes the number of nodes in the network. In-degree centrality of node I is the sum of number of nodes j in the network of (1 to l) that connected (from node j to node i). The out-degree centrality of node I is the sum of the number of nodes j in the network (1 to l) connected to the outside (from node I to node j).
Betweenness centrality measures the frequency with which a person as a public figure is active on the path between pairs of others (Timur and Getz, 2008). Among them, the node measures the extent to which it can take the role of a broker or gatekeeper with the potential to control others. The centrality among the nodes can be defined as the following equation:
Source: (Shih, 2006)
In which gjk indicates the amount of geodesic between node j and k, and gjk (n i) indicates the geodesic number connecting the two nodes containing node i. In-between centrality on node i is the sum of the estimated probability of node I to stand along the chosen geodesic by every pair of nodes (node j and k excluding node i) on the network. The centrality among the nodes i is the sum of the estimated probability of node I to stand along to the chosen geodesic by every pair of nodes (node j and k excluding node i) on the network. The central position in the network indicates the amount of power gained through the structure and the capacity to access information and other members (Carrington, Scott, et al., 2005). This study will use the centrality analysis to identify the main figures and their roles in the collaborative network of slum management in Pekanbaru.
Case study: urban slum management of PekanbaruPekanbaru is one of the cities in Indonesia which rapidly developed related to the strategic position and role in regional and national contexts. In a year, it was noted that the population of Pekanbaru increased by 4.06%. In 2016, the population of Pekanbaru City was up to 1,064,566 citizens, while in 2017, the population increased to 1,091,088 citizens. Pekanbaru population growth in 2017 was 2.49%, higher than the national population growth average of only 1.19% (BPS Pekanbaru, 2018).
Pekanbaru’s high population growth is an inseparable aspect of urban problems, which can cause urban slum settlements, high demand for water supply, sanitation, waste management, buildings, environmental problems, and poverty. Most of the slum settlements in Pekanbaru are in the city’s centre and coastal river areas with moderate and heavy slum levels. The handling of slum settlements started to be discussed in 2015, and the program’s implementation began in 2016 to 2019. This study analyses a collaborative policy network that focuses on the implementation process, which includes three stages, as listed in Table 1. The implementation analysis is performed in each stage because the influence of resources and information of policy network figures tends to differ at each stage.
| Preparation | Planning | Implementation |
|---|---|---|
|
May-November 2016 Create the local regulations, establish and strengthen the institutions and socialising programs. |
November 2016-April 2017 Preparation of integrated city documents (RP2KPKP / SIAP) and urban village documents (RPLP) |
April 2017-Desember 2019 The commitment of the city government and stakeholders to complete the program |
The preparation stage started from May to November 2016, during which the central government and the city government of Pekanbaru decided the city should have correct management regarding the urban slum management program through the regional regulations. The Mayor of Pekanbaru and related regional apparatus organisations held a meeting and discussed the formation of regional institutions and organisations from the governmental instrument to the citizens. Based on the meeting results, a working group for handling slum settlements was formed. It comprises government, private sector, society, academia, and media elements. To strengthen the institutional capacity of the working group, the city government held workshops and orientation workshops that started from the city to the village level. By carrying out the workshops and orientation workshops, it is hoped that the commitment of stakeholders will help to increase the success of the urban slum management program.
The planning stage was held from November 2016 to April 2017, during which the city government and stakeholders prepared plans for the prevention and quality improvement of urban slum settlements carried out consistently to the collaborative scheme. The result of this formulation was used as a guideline in preparing a document of residential environmental management plan at the village level. The document of the Prevention Plan contains the root formulation of the urban slum problems, the early idea of coping with slums, and the agreement on formulating a vision for urban settlements. Meanwhile, the stages of data consolidation activities produce the profiles of urban slum settlements, baseline data of slums, information on problems and potential existing slums and the verification of slum decree.
The Implementation stage from April 2017 to December 2019 includes the period of the implementation of social, economic and infrastructure activities related to the planning compiled in the Prevention Plan (urban planning document) and village planning document. The activity stages of implementation were carried out after every document was approved by the Mayor of Pekanbaru. The carried-out activities are listed in the annual plan, and the priority activities in the city and neighbourhood scales have been coordinated among various stakeholders at the city and district levels. Accordingly, this study tried to examine the dynamic changes in network structure and the roles of its public figures.
This study uses a quantitative method with a case study approach of slum settlements in Pekanbaru, Indonesia. The location was chosen because it is a national program dealing with the urban slum settlements in Indonesia. Moreover, program participants are fully accessible, a prerequisite for the intensive data collection. The subjects of this network analysis are public figures who are directly and indirectly involved in the urban slum management program of Pekanbaru. The first screening of the selected public figures was based on a public document issued by the Pekanbaru government, including the mayor of Pekanbaru decision paper No. 518 in 2018 about establishing the Housing and Settlement Area Working Group (Pokja PKP), which contains the regional apparatus organisation related to academia, private, media, and non-governmental organisations. The final selection was carried out through interviews with the actors in charge of the program. The responsible community figure is the Mayor of Pekanbaru, who was interviewed on Sept 14, 2020.
| Category (Node Name) | Community Figures/Organisation |
|---|---|
| Regional Government | City Government, Regional Secretary, Development Planning Agency at Sub-National Level, Citizen’s housing department and residential area, Department of public works and spatial planning, Central statistics institution, Environmental and hygiene services, Land Institution, District Regional Representatives, Fire Fighter (Damkar), Health Institution (Dinkes), Districts and Villages |
| Private Sector | The Association of Housing and settlement developers in Indonesia, National Housing Development of Public Company, Regional water supply company, State Electricity Company, Consultant, and Banking. |
| Society | Social self-reliance agency, Participatory planning main team, non-governmental groups, City Coordinator, district facilitator, A group of Maintenance, and Non-Governmental Organization. |
| College / Academics | Riau University, Lancang Kuning University, Islamic University of Riau, and Sultan Syarif Kasim II State Islamic University. |
| Media | Riau Pos, Tribun, Pekanbaru Pos, and Riau Newspaper |
Based on the process above, the final figures consist of regional apparatus organisations and other participants related to the program implementation. All of the actors were a formal institution of 34 organisations. The list of every organisation is mostly categorised and divided into five groups: local government, private sector, universities and academia, local organisations, and the media, as shown in Table 2.
Questionnaire and data collectionA semi-structured questionnaire was developed to measure the boundaries of community figures. Surveys and questionnaires in whole network studies use multiple response formats to obtain network data, such as binary judgments regarding the respondent within the specific relationship of each actor on the list and ordinal rank (Carrington, Scott, et al., 2005). It usually consists of two questions: (1) name generator, identifying the figures to learn from the respondent’s interpersonal environment, and (2) name interpreter, refining substantive details regarding the relationships and types of community figures in an identified environment (Dubos, 2017). Name Interpreter is a series of questions asked to obtain the required information and interpret the network figures listed in the name generator.
The questions included several items such as attributes, age, length of time they had known each other, and contact frequency. The questionnaire is organised into several items, which allows the measurement of internal and external networks. To measure the internal network, the researcher asked the respondents regarding the organisations they frequently contacted at each stage of the program. This relationship also describes the frequency and content. The frequency was classified into five groups, which included once a year, once for six months, once for 3-4 months, once a month and once a week. In order to measure the external network, the respondent was asked which organisation he was in contact with on each program. Respondents were asked to fill in the frequency of contact and its contents.
Data collection was carried out after the research objectives were explained. Questionnaires were distributed directly or via email to 34 organisations selected as community figures in Pekanbaru. A questionnaire survey was sent from Sept 21, 2020, to Nov 18, 2020, and every respondent responded to the question. The collected data was recorded through three proximity matrices of each level. The counted value was set at 0 for no collaboration relationship and 1 for any collaboration relationship. These matrix values are then measured through UCINET 6 software to calculate the network size and graphical representation among the network of community figures.
The average degree, density, and network centralisation were analysed to examine the structural characteristics of the network as a whole, as written in Table 3.
| Network Structure | Preparation | Plan | Implementation |
|---|---|---|---|
| Avg. Degree | 7 | 6.353 | 4.500 |
| Density | 0.233 | 0.193 | 0.136 |
| Network Centralisation | 48.08% | 40.37% | 28.11% |
In the preparation stage, the average degree of network relations is 7, which implies that every figure maintains a collaborative relationship with seven different community figures in the network. It means that local government and stakeholders agree and are enthusiastic about implementing this program. However, after the working group was formed, these organisations had an impression and tendency to stay steady and not quickly updated. A decreasing trend was shown in the network’s average degree of organisation relationship, where the average degree in network structure lessened to 6.353 during the planning stage and continued to drop to 4.500 during the implementation stage. It is due to Pokja not carrying the function as coordination places and driving motor, causing the relationship between collaboration and stakeholders to proceed unsmoothly.
Density is the actual line number level of every existing connection number on the network and has a value between 0 and 1 (Carrington, Scott, et al., 2005). The network density in the planning stage is represented by 0.233, indicating that the network is less dense, and each organisation is barely close to the other. In other words, the higher the density level, the higher the degree of interaction among the community figures. However, this network density condition was continually decreasing at the stage of program implementation. The decrease happens due to several barriers related to communication, exchange of information, expertise, trust, and resources among public figures.
The centralisation of the network or degree of asymmetry distribution is relatively high. In the preparation stage, the network centralisation presented at 48.08%. It reduced to 40.37% in the planning stage and continued to drop to only 28.11% during the implementation stage. This result demonstrates that the entire network is centred on the leading organisation at the main of the network.
Figure 1, Figure 2 and Figure 3 vividly depict the collaboration network in chronological order. Sociogram networks describe the relationship by identifying the position of the figure or organisation. The network nodes represent 34 organisations that were participating in the program. The connection of each node indicates the existence of interactions that maintain the relationship between organisations and institutions. One-way arrows indicate the frequency of respondents interacting with the organisations; however, other organisations do not contact them, and vice versa. Two-way arrows show that there is a reciprocal relationship occurs.
Figure 1 illustrates the collaboration in the preparation stage of the slum management program. City governments and local organisations are at the centre of the network because the information sources come from them. It can be seen from the location of nodes drawn in the box; they are gathered around the policy network. Figure 2 illustrates the network during the planning stage of the program. City governments and local organisations remain the network’s main focus because of the communication and intense coordination between them. In particular, central and suburban network structures focused on municipalities and organisations being formed. City governments and local government organisations receive and share information with other stakeholders, as shown by the arrows in Figure 1 and Figure 2.
Figure 3 illustrates the network during the implementation of the program. Compared to the previous period, the relationship density was formed only for several organisations or community figures in the regional apparatus. It can be seen from the number of aimed arrows. It means that the policy network starts to converge only for several organisations or figures. For example, Dinas Perkim, PUPR and Sub-District was the main actor of implementer activity in Indonesia. Besides, there are quite significant changes that occurred in government, where the relationship has begun to lose and has not become one of the focuses of the network.
Centrality analysis The preparation stage of the programTable 4 indicates the results of the centrality level analysis on the program preparation stage. In-degree level refers to accepting requests for relationships from other figures. The top five positions are taken in the analysis, such as City Government, National Development Institution (Bappeda), Housing and Settlement Institution (Perkim), The Ministry of Public Works and Housing (PUPR), and District that shows high indicators of centrality. A high centrality level indicates the amount of direct collaboration with the highest number.
| Rank | Actor/Organisation | Out-degree | Rank | Figure/Organisation | In-degree |
|---|---|---|---|---|---|
| 1 | City Government | 26.000 | 1 | City Government | 30.000 |
| 2 | Regional Development Institution (Bappeda) | 16.000 | 2 | The Ministry of Public Works and Housing (PUPR) | 17.000 |
| 3 | Housing and Settlement Institution (Perkim) | 14.000 | 3 | National Development Institution (Bappeda) | 16.000 |
| 4 | The Ministry of Public Works and Housing (PUPR) | 13.000 | 4 | Housing and Settlement Institution (Perkim) | 16.000 |
| 5 | District | 11.000 | 5 | District | 14.000 |
As shown in Table 4, the Pekanbaru government is currently placed in the first rank for the out-degree and in-degree. The Ministry of Public Works and Housing is in second place in In-degree. Every three or four months, the City Government communicates with the Regional Development Institution (Bappeda), Housing and Settlement Institution (Perkim), Ministry of Public Works and Housing (PUPR), and District to discuss the institutional strength and location of slum settlements. As the second place of out-degree, the Regional Development Institution (Bappeda) interacts and consults with the Ministry of Public Works and Housing (PUPR) and Housing and Settlement Institution (Perkim) once every three or four months to establish the criteria for slum areas. Housing and Settlement Institution (Perkim), ranked third place of out-degree, participated in the exchange of information and provided input to the districts to succeed in the socialisation of slum settlements.
Table 5 shows the betweenness centrality analysis result. The top five positions as betweenness organisation consist of the City Government, Regional Development Institution (Bappeda), The Ministry of Public Works and Housing (PUPR), Housing and Settlement Institution (Perkim) and non-governmental organisations. Generally, this result indicated that the city government has the main role of mediating the information and resources among every figure or organisation of the policy network.
| Rank | Organisation | Betweenness Centrality |
|---|---|---|
|
1 2 3 4 5 |
City Government National Development Institution (Bappeda) The Ministry of Public Works and Housing (PUPR) Housing and Settlement Institution (Perkim) LSM |
49.454 8.736 6.314 6.314 3.316 |
The planning stage of the program was done during the specified time, November 2016 to April 2017. During that time, five work levels of meetings were held to produce the suitable work plans, survey design and activity format, the overview of regional policies, identification of the suitability of settlements city spatial plans, coordination and synchronisation of the slum settlement data, the preparation of technical designs which include preparation of detailed site plans and the preparation of design support visuals, the list of detailed measurement of infrastructure components, and the organisation detailed engineering design (DED).
Table 6 shows the results of the centrality degree analysis in the project planning stage. Housing and Settlement Institution (Perkim) ranked first place of centrality both in-degree and out-degree. The Housing and Settlement Institution (Perkim) communicates and collaborates with the Ministry of Public Works and Housing (PUPR) and the City Government every month to discuss the technical design and detailed engineering designs that will be used in the implementation of slum management collaboration. Besides, the Housing and Settlement Institution (Perkim) is also related to the Regional Development Institution (Bappeda) to formulate the management scenarios and area design concepts. It aims to formulate action plans and program integration memoranda for the city and area. The Ministry of Public Works and Housing (PUPR), as the second rank in centrality degree, related to TIPP of the society every month to get information about the required infrastructure of society and discuss the work plans. TIPP, along with the Regional Development Institution (Bappeda), as the third rank in the degree of centrality, influenced the city government to control various resources and financial support in the network. Therefore, they hold intense meetings every month.
| Rank | Organisation | Out-degree | Rank | Organisation | In-degree |
|---|---|---|---|---|---|
| 1 | Housing and Settlement Institution (Perkim) | 17.000 | 1 | Housing and Settlement Institution (Perkim) | 20.000 |
| 2 | City Government | 15.000 | 2 | The Ministry of Public Works and Housing (PUPR) | 20.000 |
| 3 | The Ministry of Public Works and Housing (PUPR) | 15.000 | 3 | City Government | 18.000 |
| 4 | TIPP | 14.000 | 4 | National Development Institution (Bappeda) | 16.000 |
| 5 | National Development Institution (Bappeda) | 14.000 | 5 | TIPP | 14.000 |
Table 7 shows the results of betweenness centrality analysis. The top five organisations of the betweenness centralities for the program planning stage consist of the city government, the Housing and Settlement Institution (Perkim), the Regional Development Institution (Bappeda), The Ministry of Public Works and Housing (PUPR), TIPP (Participatory Planning Core Team). Like the preparation team, the organisation below holds the top five position of betweenness centrality on the planning program. These results indicate that the city government is the main figure of the network. The role of community figures or organisations in the network is the main focus with the most frequent communication intensity. In the other world, they hold an essential position in program planning.
| Rank | Organisation | Betweenness Centrality |
|---|---|---|
|
1 2 3 4 5 |
City Government Housing and Settlement Institution (Perkim) The Ministry of Public Works and Housing (PUPR) National Development Institution (Bappeda) TIPP |
23.898 16.249 11.314 10.803 9.815 |
The implementation stage was carried out through collaborative interactions between the involved organisations for both formal and informal members. Table 8 indicates the level of centrality in the implementation stage.
For the centrality degree, the out-degree rank was respectively occupied by the Ministry of Public Works and Housing (PUPR), Housing and Settlement Institution (Perkim), Sub-district, District and Facilitator. Meanwhile, the degree of centrality of the internal relationship was obtained by the Housing and Settlement Institution (Perkim), the Ministry of Public Works and Housing (PUPR), the Sub-district, the District, and facilitators.
| Rank | Figure/Organisation | Out-degree | Rank | Figure/Organisation | In-degree |
|---|---|---|---|---|---|
| 1 | The Ministry of Public Works and Housing (PUPR) | 19.000 | 1 | Housing and Settlement Institution (Perkim) | 24.000 |
| 2 | Housing and Settlement Institution (Perkim) | 19.000 | 2 | The Ministry of Public Works and Housing (PUPR) | 19.000 |
| 3 | Sub-District | 17.000 | 3 | Sub-District | 17.000 |
| 4 | District | 8.000 | 4 | District | 11.000 |
| 5 | Facilitator | 7.000 | 5 | Facilitator | 7.000 |
The Ministry of Public Works and Housing (PUPR), which has the highest rank of centrality, actively shares information and resources with Housing and Settlement Institution (Perkim), Sub-District and local media to inform the progress regarding activities implementation. Housing and Settlement Institution (Perkim), the first rank of centrality in-degree, receives information from the Sub-district, District and Facilitator. As the third place of out-degree centralisation, the sub-district establishes the communication and sharing of information with the District and Facilitator. Sub-district is an area where the environmental settlement implementation was carried out. Meanwhile, the facilitator is the community figure who connects the communication between citizens and the government. They actively discuss, interact, and collaborate to complete the management program. Table 9 shows the results of the betweenness centrality analysis as below.
| Rank | Figure/Organisation | Betweenness |
|---|---|---|
|
1 2 3 4 5 |
Sub-District Housing and Settlement Institution (Perkim) The Ministry of Public Works and Housing (PUPR) National Development Institution (Bappeda) District |
30.300 29.239 21.197 7.465 4.662 |
During the implementation phase of the program, the five organisations that have the highest betweenness centrality are the Sub-District, Housing and Settlement Institution (Perkim), The Ministry of Public Works and Housing (PUPR), Regional Development Institution (Bappeda), and District. Sub-districts come out as the main organisation that holds the top position for betweenness centrality, replacing the role of city government and taking an important role as the intermediary that connects and collaborates with every organisation of the network.
As described before, collaborative policy networks were explained by the formation of local government communities, the private sector, academics, and the media. The connection among the organisations is a communication channel to the information, expertise, trust, and policy resources, and the limitations of the policy network that the formal institutions did not determine —however, the results of the process related to each other on functional relevance and structural bound.
In the preparation stage of activity program, the government of Pekanbaru has the highest ranking in every degree of centrality. The city government has a close relationship with every regional apparatus organisation of the society, reflected in the network. Besides, the Pekanbaru government also ranks the highest in betweenness centrality. It is indicated that the Pekanbaru government takes the leading role in mediating every figure of the network. During this preparation stage, there were many relationships among the government, private institutions, citizens, academic and media organisations. In other words, the relationship among the figures has been formed within the exchange of information, expertise, trust, and policy resources.
Furthermore, in the planning stage, the Housing and Settlement Institution (Perkim) appeared in the highest ranking of both in-degree and out-degree. The Housing and Settlement Institution (Perkim)’s role is increasing at this stage. It is inseparable from their resources and abilities. Their resources and expertise are considered important to produce technical designs, including detailed maps and site plans, visualisation of design support, list of plans and detailed measurements of infrastructure components, and preparation of detailed engineering designs.
For the betweenness centrality, the city government has not been replaced. The primary role of city government as the leading figure was to connect the government interest and citizens in society in order to synchronise the planning activities through the preparation of Urban Slum Settlement Prevention and Quality Improvement. Therefore, collaboration between government, public and private sectors is vital in planning. Moreover, the results of this planning stage will determine the success of the implementation stage.
In the implementation of the program, both The Ministry of Public Works and Housing (PUPR) and Housing and Settlement Institution (Perkim) got the first rank in terms of out-degree centralisation because these organisations have the same influence on providing enthusiastic information and also took an active role in communicating with other stakeholders. However, regarding internal relationship centrality, the Housing and Settlement Institution (Perkim) ranks higher than the Ministry of Public Works and Housing (PUPR) due to the large number of requests for consultation and information required by other stakeholders.
Related to the centrality in the program implementation, the Sub-district is the leading figure in mediating the relationship of every community figure or organisation. Sub-district is the lowest government organisation that is directly related to the process of handling the slum settlements. Moreover, other organisations will be connected to the sub-district to obtain the data and information on handling the slum settlements. It implies that there has been a dynamic relationship happening in the network.
From the three stages of slum management programs, it can be seen that the dynamics and patterns of the network were formed. The slum management collaborative network forms a complex pattern. The amount of organisation that participates is relatively stable; however, as the program progresses, there is a decrease in distance and density in collaborative relationships between the involved figures. Regional government comes out as the principal figure that holds the control to lead other figures. Local governments have taken the initiative in structuring and controlling large amounts of resources and information, especially at every activity stage. Local government ranks highest in degree centrality and betweenness centrality. Thus, the distribution of power is needed to maintain the stability of the network.
This study contributes by providing an understanding of the dynamics of policy networks by analysing the characteristics and roles of collaborative policy networks in handling the slum settlements by the social network analysis method. The main community figures are identified regarding their roles in the collaborative process that will provide the required basic foundation for planning and implementing the policies of slum management. The social network analysis method provides an avenue to carefully examine the workings of collaborative policy networks.
From the three undertaken stages, the local government emerged as the leading figure that held the role and controlled every information and resource in the network. Besides, the dynamics and patterns of the slum management collaboration network tend to be centred only on a few local government figures. The distance and density of relations also indicate a declining trend at every stage of activity. Therefore, to make the policy network function properly, equity of resources, information, and leadership roles are needed in facilitating and balancing the collaborative competition. Thus, it is expected that the active participation of other stakeholders will be realised to balance the dominance of local government. Hence, the local governments need to encourage the formation of mechanisms and connections so that other stakeholders can actively participate in the slum management activity program.
Furthermore, this case study emphasises the importance of leadership role in its collaboration of handling the slum settlement. In reality, the local government has shown dominance over other members in implementing the program, even though this program initially formed a working group consisting of public institution members, private institution members, citizens, academia and media sectors. Thus, in the future, active participation from stakeholders is required, especially for the private sector, which has not played an active role in this program. Besides, the actor involvement or another non-formal institution is equally important in collaborative relations, utilising its expertise and resources to further legitimise slum settlement policies in Pekanbaru City.
Conceptualisation, SZ; methodology, SZ; validation, SZ; formal analysis, SZ; investigation, SZ; data curation, SZ; writing—original drafting, SZ; project administration, SZ, BR, RAB, and YSS; supervise, SZ, BR, RAB, and YSS. All authors have read and agree to the published version of the manuscript.
The authors declare that they have no conflicts of interest regarding the publication of the paper.
The authors thank the anonymous reviewers for their valuable reviews and suggestions. The authors also thank the Ministry of Research, Technology and Higher Education of the Republic of Indonesia through the Domestic Postgraduate Education Scholarship (BPPDN) for supporting this research.
